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Code for Cicero, an AI agent that plays the game of Diplomacy
The project is the codebase for an AI agent named Cicero developed by Facebook Research. It is designed to play the board game Diplomacy by combining open-domain natural language negotiation with strategic planning. The repository includes training code, model checkpoints, and infrastructure for both language modelling (via the ParlAI framework) and reinforcement learning for strategy agents.
AI agent memory system—pure Markdown, zero dependencies, fully local
MUSE gives AI coding agents persistent cross-session memory and multi-role governance through plain Markdown files.
Supports Claude Code, OpenClaw, Cursor, Windsurf, Gemini CLI, and Codex via one-command install. Built-in MCP Server for programmatic access.
56 skills, auto memory capture, semantic compression, role-based governance, multi-project management.